International Journal of Computers and Applications

FAULT ANALYSIS OF TRANSMISSION LINE BASED ON BIG DATA ALGORITHM, 216-223. Keywords Big data analysis, transmission line fault, intelligent algorithm, faultanalysis, line fault analysis Abstract Transmission lines are an important part of the power system. The application of online monitoring technology for transmission lines has produced a large amount of line operation data. This article mainly analyses and researches transmission line faults based on big data algorithms.

FAULT ANALYSIS OF TRANSMISSION LINE BASED ON BIG DATA ALGORITHM, 216-223. References [1] Z. Lv, H. Song, P. Basanta-Val, A. Steed, and M. Jo, Next-generation big data analytics: State of the art, challenges, and future research topics, IEEE Transactions on Industrial Informatics, 13(4), 2017, 1891–1899, doi: 10.1109/TII.2017.2650204. 7 223 [2] M.

FAULT ANALYSIS OF TRANSMISSION LINE BASED ON BIG DATA ALGORITHM, 216-223. Keywords Big data analysis, transmission line fault, intelligent algorithm, faultanalysis, line fault analysis Abstract Transmission lines are an important part of the power system. The application of online monitoring technology for transmission lines has produced a large amount of line operation data. This article mainly analyses and researches transmission line faults based on big data algorithms.

STRUCTURE AND TUNING OF OBSERVER-BASED PID, 205-215. Keywords Observer-based PID, first-order plus dead-time, parameter tuning,PID + filter, temperature control lab Abstract The proportional–integral–derivative (PID) is the most widely used control structure in the industry.

A NOVEL EMD-IABC BASED DE-NOISING FOR GRAIN IMPACT SIGNAL, 197-204. Keywords Grain impact, EMD, ABC, threshold optimisation Abstract To remove noise from the grain impact signal, a de-noising method that incorporates empirical mode decomposition (EMD) and artificial bee colony (ABC) is proposed. EMD decomposes a signal into intrinsic mode functions (IMFs) that are with different frequencies. The de-noising signal is obtained by superposition of the IMFs processed with a threshold set.

STRUCTURE AND TUNING OF OBSERVER-BASED PID, 205-215. Keywords Observerbased PID, firstorder plus deadtime, parameter tuning,PID + filter, temperature control lab Abstract The proportional–integral–derivative (PID) is the most widely used control structure in the industry.

A NOVEL EMD-IABC BASED DE-NOISING FOR GRAIN IMPACT SIGNAL, 197-204. Keywords Grain impact, EMD, ABC, threshold optimisation Abstract To remove noise from the grain impact signal, a de-noising method that incorporates empirical mode decomposition (EMD) and artificial bee colony (ABC) is proposed. EMD decomposes a signal into intrinsic mode functions (IMFs) that are with different frequencies. The de-noising signal is obtained by superposition of the IMFs processed with a threshold set.

FAULT ANALYSIS OF TRANSMISSION LINE BASED ON BIG DATA ALGORITHM Keywords Big data analysis, transmission line fault, intelligent algorithm, faultanalysis, line fault analysis Abstract Transmission lines are an important part of the power system. The application of online monitoring technology for transmission lines has produced a large amount of line operation data. This article mainly analyses and researches transmission line faults based on big data algorithms.

FAULT ANALYSIS OF TRANSMISSION LINE BASED ON BIG DATA ALGORITHM References [1] Z. Lv, H. Song, P. Basanta-Val, A. Steed, and M. Jo, Next-generation big data analytics: State of the art, challenges, and future research topics, IEEE Transactions on Industrial Informatics, 13(4), 2017, 1891–1899, doi: 10.1109/TII.2017.2650204. 7 [2] M. Alomoush, Optimal damping controllers in a power system including TCSC using gravitational search algorithm, Mechatronic Systems and Control, 47(1), 2019, 18–27. [3] L.

A NOVEL EMD-IABC BASED DE-NOISING FOR GRAIN IMPACT SIGNAL Keywords Grain impact, EMD, ABC, threshold optimisation Abstract To remove noise from the grain impact signal, a de-noising method that incorporates empirical mode decomposition (EMD) and artificial bee colony (ABC) is proposed. EMD decomposes a signal into intrinsic mode functions (IMFs) that are with different frequencies. The de-noising signal is obtained by superposition of the IMFs processed with a threshold set.